Maternal n-3 enriched diet reprograms the offspring neurovascular transcriptome and blunts inflammation induced by endotoxin in the neonate.

Infection during the perinatal period can adversely affect brain development, predispose infants to ischemic stroke and have lifelong consequences. We previously demonstrated that diet enriched in n-3 polyunsaturated fatty acids (n-3 PUFA) transforms brain lipid composition in the offspring and protects the neonatal brain from stroke, in part by blunting injurious immune responses. Critical to the interface between the brain and systemic circulation is the vasculature, endothelial cells in particular, that support brain homeostasis and provide a barrier to systemic infection. Here, we examined whether maternal PUFA-enriched diets exert reprograming of endothelial cell signalling in postnatal day 9 mice after modeling aspects of infection using LPS. Transcriptome analysis was performed on microvessels isolated from brains of pups from dams maintained on 3 different maternal diets from gestation day 1: standard, n-3 enriched or n-6 enriched diets. Depending on the diet, in endothelial cells LPS produced distinct regulation of pathways related to immune response, cell cycle, extracellular matrix, and angiogenesis. N-3 PUFA diet enabled higher immune reactivity in brain vasculature, while preventing imbalance of cell cycle regulation and extracellular matrix cascades that accompanied inflammatory response in standard diet. Cytokine analysis revealed a blunted LPS response in blood and brain of offspring from dams on n-3 enriched diet. Analysis of cerebral vasculature in offspring in vivo revealed no differences in vessel density. However, vessel complexity was decreased in response to LPS at 72 h in standard and n-6 diets. Thus, LPS modulates specific transcriptomic changes in brain vessels of offspring rather than major structural vessel characteristics during early life. N-3 PUFA-enriched maternal diet in part prevents an imbalance in homeostatic processes, alters inflammation and ultimately mitigates changes to the complexity of surface vessel networks that result from infection. Importantly, maternal diet may presage offspring neurovascular outcomes later in life.

Dilated lenticulostriate artery on whole-brain vessel wall imaging differentiates pathogenesis and predicts clinical outcomes in single subcortical infarction.

OBJECTIVES: This study aimed to investigate the dilation of lenticulostriate artery (LSA) identified by whole-brain vessel wall imaging (WB-VWI) in differentiating the etiologic subtypes of single subcortical infarction (SSI) and to determine whether the appearance of dilated LSA was associated with 90-day clinical outcomes in parental atherosclerotic disease (PAD)-related SSI. METHODS: Patients with acute SSI were prospectively enrolled and categorized into PAD-related SSI and cerebral small-vessel disease (CSVD)-related SSI groups. The imaging features of LSA morphology (branches, length, dilation, and tortuosity), plaques (burden, remodeling index, enhancement degree, and hyperintense plaque), and CSVD (white matter hyperintensity, lacunes, cerebral microbleed, and enlarged perivascular space) were evaluated. The logistic regression was performed to determine the association of dilated LSA with PAD-related SSI and 90-day clinical outcomes. RESULTS: In total, 131 patients (mean age, 52.2 ± 13.2 years; 99 men) were included. The multivariate logistic regression analysis revealed that the presence of dilated LSAs (odds ratio (OR), 7.40; 95% confidence interval (CI): 1.88-29.17; p = 0.004)) was significantly associated with PAD-related SSI. Moreover, after adjusting for confounding factors, the association of poor outcomes with the total length of LSAs (OR, 0.94; 95% CI: 0.90-0.99; p = 0.011), dilated LSAs (OR, 0.001; 95% CI: 0.0001-0.08; p = 0.002), and plaque burden (OR, 1.35; 95% CI: 1.11-1.63; p = 0.002) remained statistically significant. CONCLUSION: The dilation of LSA visualized on WB-VWI could differentiate various subtypes of SSI within LSA territory and was a prognostic imaging marker for 90-day clinical outcomes for PAD-related SSI. CLINICAL RELEVANCE STATEMENT: Evaluation of LSA morphology based on WB-VWI can differentiate the pathogenesis and predict clinical outcomes in SSI, providing crucial insights into the etiologic mechanisms, risk stratification, and tailored therapies for these patients. KEY POINTS: The prognosis of SSIs within lenticulostriate territory depend on the etiology of the disease. LSA dilation on WB-VWI was associated with parental atherosclerosis and better 90-day outcomes. Accurately identifying the etiology of SSIs in lenticulostriate territory assists in treatment decision-making.

Large vessel occlusion detection by non-contrast CT using artificial intelligence.

INTRODUCTION: Computer vision models have been used to diagnose some disorders using computer tomography (CT) and magnetic resonance (MR) images. In this work, our objective is to detect large and small brain vessel occlusion using a deep feature engineering model in acute of ischemic stroke. METHODS: We use our dataset. which contains 324 patient's CT images with two classes; these classes are large and small brain vessel occlusion. We divided the collected image into horizontal and vertical patches. Then, pretrained AlexNet was utilized to extract deep features. Here, fc6 and fc7 (sixth and seventh fully connected layers) layers have been used to extract deep features from the created patches. The generated features from patches have been concatenated/merged to generate the final feature vector. In order to select the best combination from the generated final feature vector, an iterative selector (iterative neighborhood component analysis-INCA) has been used, and this selector has chosen 43 features. These 43 features have been used for classification. In the last phase, we used a kNN classifier with tenfold cross-validation. RESULTS: By using 43 features and a kNN classifier, our AlexNet-based deep feature engineering model surprisingly attained 100% classification accuracy. CONCLUSION: The obtained perfect classification performance clearly demonstrated that our proposal could separate large and small brain vessel occlusion detection in non-contrast CT images. In this aspect, this model can assist neurology experts with the early recanalization chance.

Long-term organotypic brain slices cultured on collagen-based microcontact prints: A perspective for a brain-on-a-chip.

Organotypic brain slices are three-dimensional 150 µm-thick sections of a postnatal day 10 mouse and can be cultured for several weeks in vitro. In such brain slices the complex cellular connections are preserved with a high viability. These brain slices can be connected to collagen-loaded microcontact prints to develop a simple brain-on-a-chip model. Using the microcontact printing technique, many peptides or proteins can be printed onto a semipermeable membrane and linked to brain slices. On these microcontact prints, brain-derived nerve fibers grow out, or microglia can get activated and migrate out, or also new brain vessels can be formed. Such a brain-on-a-chip model may allow to develop new drugs or a diagnostic method for neurodegenerative diseases.

Diagnostic Value of Computed Tomography Angiography in Confirmation of Brain Death.

BACKGROUND: Accurate and on-time confirmation of brain death (BD) is necessary to prevent unnecessary treatment and allow for well-timed organ harvest for transplantation. Although the clinical criteria for BD are legally reliable in some countries, others might prefer complementary ancillary tests to assess the brain's electrical activity and/or blood circulation. The present study aims to define the sensitivity and specificity of computed tomography angiography using 4-, 7-, and 10-point tests compared with the clinical criteria and electroencephalographic findings in patients with BD. METHODS: A total of 32 patients with a confirmed diagnosis of BD according to their clinical criteria (cases) and 18 patients with a Glasgow coma scale score of 3 and absent brain stem and papillary reflexes who had spontaneous respiration (controls) were included in the present study. All the patients had blood pressure >90 mm Hg, diuresis >100 mL/hour, and central venous pressure >6-8 mm Hg, and undergone computed tomography angiography (CTA). The 4-, 6-, and 10-point criteria were used to determine the opacity and lack of opacity of the brain vessels in the CTA evaluation scales for the diagnosis of BD. RESULTS: The 2 groups were homogeneous in terms of age, gender distribution, and coma etiology. All 18 patients in the control group received a score of 0 in the 4-, 7-, and 10-point scores. In contrast, the average values for the 4-, 7-, and 10-point scores for the patients with confirmed BD were 3.75 ± 0.67, 6.4 ± 1.36, and 9.06 ± 2.2, respectively. Of the patients with BD, 28 (87.5%), 26 (81.25%), and 25 (78.12%) received the full score for the 4-point, 7-point, and 10-point tests. The sensitivity, specificity, and negative and positive predictive values for all 3 scores were 100%. Also, the sensitivity for the various cerebral vessels were as follows: internal cerebral vein, 100%; great cerebral vein, 96.9%; posterior 2, 90.6%, middle 4, 87.5%; basilar artery, 84.4%; and anterior 3, 84.4%. Finally, the specificity for the lack of opacification in all these vessels for the diagnosis of BD was 100%. CONCLUSIONS: According to our findings, the CTA-based 4-point scoring system with 100% specificity can be used with the clinical examination findings to confirm BD.

Deep reinforcement learning for cerebral anterior vessel tree extraction from 3D CTA images.

Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and computed tomography perfusion (CTP) images. To this end, we regard the anterior vessel tree as a set of bifurcations and connected centerlines. The method consists of a proximal policy optimization (PPO) based deep reinforcement learning (DRL) approach for tracking centerlines, a convolutional neural network based bifurcation detector, and a breadth-first vessel tree construction approach taking the tracking and bifurcation detection results as input. We experimentally determine the added values of various components of the tracker. Both DRL vessel tracking and CNN bifurcation detection were assessed in a cross validation experiment using 115 subjects. The anterior vessel tree formation was evaluated on an independent test set of 25 subjects, and compared to interobserver variation on a small subset of images. The DRL tracking result achieves a median overlapping rate until the first error (1.8 mm off the reference standard) of 100, [46, 100] % on 8032 vessels over 115 subjects. The bifurcation detector reaches an average recall and precision of 76% and 87% respectively during the vessel tree formation process. The final vessel tree formation achieves a median recall of 68% and precision of 70%, which is in line with the interobserver agreement.

Beta-Amyloid Enhances Vessel Formation in Organotypic Brain Slices Connected to Microcontact Prints.

In Alzheimer's disease, the blood-brain barrier breakdown, blood vessel damage and re-organization are early events. Deposits of the small toxic peptide beta-amyloid (Aß) cause the formation of extracellular plaques and accumulate in vessels disrupting the blood flow but may also play a role in blood clotting. In the present study, we aim to explore the impact of Aß on the migration of endothelial cells and subsequent vessel formation. We use organotypic brain slices of postnatal day 10 wildtype mice (C57BL/6) and connect them to small microcontact prints (µCPs) of collagen. Our data show that laminin-positive endothelial cells migrate onto collagen µCPs, but without any vessel formation after 4 weeks. When the µCPs are loaded with human Aß40, (aggregated) human Aß42 and mouse Aß42 peptides, the number and migration distance of endothelial cells are significantly reduced, but with a more pronounced subsequent vessel formation. The vessel formation is verified by zonula occludens (ZO)-1 and -2 stainings and confocal microscopy. In addition, the vessel formation is accompanied by a stronger GFAP-positive astroglial formation. Finally, we show that vessels can grow towards convergence when two opposed slices are connected via microcontact-printed lanes. In conclusion, our data show that Aß promotes vessel formation, and organotypic brain slices connected to collagen µCPs provide a potent tool to study vessel formation.

Toward Sharing Brain Images: Differentially Private TOF-MRA Images With Segmentation Labels Using Generative Adversarial Networks.

Sharing labeled data is crucial to acquire large datasets for various Deep Learning applications. In medical imaging, this is often not feasible due to privacy regulations. Whereas anonymization would be a solution, standard techniques have been shown to be partially reversible. Here, synthetic data using a Generative Adversarial Network (GAN) with differential privacy guarantees could be a solution to ensure the patient's privacy while maintaining the predictive properties of the data. In this study, we implemented a Wasserstein GAN (WGAN) with and without differential privacy guarantees to generate privacy-preserving labeled Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) image patches for brain vessel segmentation. The synthesized image-label pairs were used to train a U-net which was evaluated in terms of the segmentation performance on real patient images from two different datasets. Additionally, the Fréchet Inception Distance (FID) was calculated between the generated images and the real images to assess their similarity. During the evaluation using the U-Net and the FID, we explored the effect of different levels of privacy which was represented by the parameter ϵ. With stricter privacy guarantees, the segmentation performance and the similarity to the real patient images in terms of FID decreased. Our best segmentation model, trained on synthetic and private data, achieved a Dice Similarity Coefficient (DSC) of 0.75 for ϵ = 7.4 compared to 0.84 for ϵ = ∞ in a brain vessel segmentation paradigm (DSC of 0.69 and 0.88 on the second test set, respectively). We identified a threshold of ϵ <5 for which the performance (DSC <0.61) became unstable and not usable. Our synthesized labeled TOF-MRA images with strict privacy guarantees retained predictive properties necessary for segmenting the brain vessels. Although further research is warranted regarding generalizability to other imaging modalities and performance improvement, our results mark an encouraging first step for privacy-preserving data sharing in medical imaging.

Generating 3D TOF-MRA volumes and segmentation labels using generative adversarial networks.

Deep learning requires large labeled datasets that are difficult to gather in medical imaging due to data privacy issues and time-consuming manual labeling. Generative Adversarial Networks (GANs) can alleviate these challenges enabling synthesis of shareable data. While 2D GANs have been used to generate 2D images with their corresponding labels, they cannot capture the volumetric information of 3D medical imaging. 3D GANs are more suitable for this and have been used to generate 3D volumes but not their corresponding labels. One reason might be that synthesizing 3D volumes is challenging owing to computational limitations. In this work, we present 3D GANs for the generation of 3D medical image volumes with corresponding labels applying mixed precision to alleviate computational constraints. We generated 3D Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) patches with their corresponding brain blood vessel segmentation labels. We used four variants of 3D Wasserstein GAN (WGAN) with: 1) gradient penalty (GP), 2) GP with spectral normalization (SN), 3) SN with mixed precision (SN-MP), and 4) SN-MP with double filters per layer (c-SN-MP). The generated patches were quantitatively evaluated using the Fréchet Inception Distance (FID) and Precision and Recall of Distributions (PRD). Further, 3D U-Nets were trained with patch-label pairs from different WGAN models and their performance was compared to the performance of a benchmark U-Net trained on real data. The segmentation performance of all U-Net models was assessed using Dice Similarity Coefficient (DSC) and balanced Average Hausdorff Distance (bAVD) for a) all vessels, and b) intracranial vessels only. Our results show that patches generated with WGAN models using mixed precision (SN-MP and c-SN-MP) yielded the lowest FID scores and the best PRD curves. Among the 3D U-Nets trained with synthetic patch-label pairs, c-SN-MP pairs achieved the highest DSC (0.841) and lowest bAVD (0.508) compared to the benchmark U-Net trained on real data (DSC 0.901; bAVD 0.294) for intracranial vessels. In conclusion, our solution generates realistic 3D TOF-MRA patches and labels for brain vessel segmentation. We demonstrate the benefit of using mixed precision for computational efficiency resulting in the best-performing GAN-architecture. Our work paves the way towards sharing of labeled 3D medical data which would increase generalizability of deep learning models for clinical use.

Piezo1-Mediated Ca2+ Activities Regulate Brain Vascular Pathfinding during Development.

During development, endothelial tip cells (ETCs) located at the leading edge of growing vascular plexus guide angiogenic sprouts to target vessels, and thus, ETC pathfinding is fundamental for vascular pattern formation in organs, including the brain. However, mechanisms of ETC pathfinding remain largely unknown. Here, we report that Piezo1-mediated Ca2+ activities at primary branches of ETCs regulate branch dynamics to accomplish ETC pathfinding during zebrafish brain vascular development. ETC branches display spontaneous local Ca2+ transients, and high- and low-frequency Ca2+ transients cause branch retraction through calpain and branch extension through nitric oxide synthase, respectively. These Ca2+ transients are mainly mediated by Ca2+-permeable Piezo1 channels, which can be activated by mechanical force, and mutating piezo1 largely impairs ETC pathfinding and brain vascular patterning. These findings reveal that Piezo1 and downstream Ca2+ signaling act as molecular bases for ETC pathfinding and highlight a novel function of Piezo1 and Ca2+ in vascular development.

Collagen hydrogels loaded with fibroblast growth factor-2 as a bridge to repair brain vessels in organotypic brain slices.

Vessel damage is a general pathological process in many neurodegenerative disorders, as well as spinal cord injury, stroke, or trauma. Biomaterials can present novel tools to repair and regenerate damaged vessels. The aim of the present study is to test collagen hydrogels loaded with different angiogenic factors to study vessel repair in organotypic brain slice cultures. In the experimental set up I, we made a cut on the organotypic brain slice and tested re-growth of laminin + vessels. In the experimental set up II, we cultured two half brain slices with a gap with a collagen hydrogel placed in between to study endothelial cell migration. In the experimental set up I, we showed that the number of vessels crossing the cut was tendencially increased with the addition of fibroblast growth factor-2 (FGF-2), vascular endothelial growth factor, or platelet-derived growth factor-BB compared to the control group. In the experimental set up II, we demonstrated that a collagen hydrogel loaded with FGF-2 resulted in a significantly increased number of migrated laminin + cells in the gap between the slices compared to the control hydrogel. Co-administration of several growth factors did not further potentiate the effects. Taken together, we show that organotypic brain slices are good models to study brain vessels and FGF-2 is a potent angiogenic factor for endothelial cell proliferation and migration. Our results provide evidence that the collagen hydrogels can be used as an extracellular matrix for the vascular endothelial cells.

Connexin 30 is expressed in a subtype of mouse brain pericytes.

Pericytes are mural cells of blood microvessels which play a crucial role at the neurovascular interface of the central nervous system. They are involved in the regulation of blood-brain barrier integrity, angiogenesis, clearance of toxic metabolites, capillary hemodynamic responses, and neuroinflammation, and they demonstrate stem cell activity. Morphological and molecular studies to characterize brain pericytes recently pointed out some heterogeneity in pericyte population. Nevertheless, a clear definition of pericyte subtypes is still lacking. Here, we demonstrate that a fraction of brain pericytes express Connexin 30 (Cx30), a gap junction protein, which, in the brain parenchyma, was thought to be exclusively found in astrocytes. Cx30 could thus be a candidate protein in the composition of the gap junction channels already described between endothelial cells and pericytes. It could also form hemichannels or acts in a channel-independent manner to regulate pericyte morphology, as already observed in astrocytes. Altogether, our results suggest that Cx30 defines a novel brain pericyte subtype.

Age-Dependent Susceptibility to Alcohol-Induced Cerebral Artery Constriction.

BACKGROUND: Age has been recognized as an important contributor into susceptibility to alcohol-driven pathology. PURPOSE: We aimed at determining whether alcohol-induced constriction of cerebral arteries was age-dependent. STUDY DESIGN: We used rat middle cerebral artery (MCA) in vitro diameter monitoring, patch-clamping and fluorescence labeling of myocytes to study an age-dependent increase in the susceptibility to alcohol in 3 (50 g), 8 (250 g), and 15 (440 g) weeks-old rats. RESULTS: An age-dependent increase in alcohol-induced constriction of MCA could be observed in absence of endothelium, which is paralleled by an age-dependent increase in both protein level of the calcium-/voltage-gated potassium channel of large conductance (BK) accessory ß1 subunit and basal BK channel activity. Ethanol-induced BK channel inhibition is increased with age. CONCLUSIONS: We demonstrate an increased susceptibility of MCA to ethanol-induced constriction in a period equivalent to adolescence and early adulthood when compared to pre-adolescence. Our work suggests that BK ß1 constitutes a significant contributor to age-dependent changes in the susceptibility of cerebral arteries to ethanol.